What the data for this category looks like
The data for this category typically comes from elderly care service information platforms, civil affairs statistics systems, fire safety inspection records, and institution operation ledgers. The update frequency is monthly. Commonly processed documents include elderly care institution filing materials, operation subsidy application forms, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. Document fields mostly cover institution names, bed counts, rectification time limits, subsidy amounts, and similar details. There are no unified fixed units, and matching must be done based on specific business scenarios.
What constraints these characteristics impose on the "workflow orchestration" link
Monthly updated data sources require workflow configuration of regular full synchronization tasks to avoid data lag. Multi-department collaborative data sources require setting cross-system data pull nodes in the workflow to integrate inspection and operation data from different channels. Diverse business document types require configuring extraction rules adapted to different fields, to match the fields of different documents such as filings and subsidy applications. Time-consuming verification links can be automated via workflows to reduce the risk of manual errors. Verification nodes must also be configured to intercept abnormal data and prevent subsequent errors.
How to configure the settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Search Filter Reference Quota Upper Limit | Top 10 entries | Elderly care supervision inquiries mostly target single-institution business, so excessive redundant data is unnecessary, avoiding token limit exceedance |
| Single Search Quota Upper Limit | Top 8 entries | Matches the scale of monthly updated data sources, balancing recall accuracy and response speed |
| Maximum Context | 1500–2000 tokens | Adapts to the context requirements of long documents such as elderly care subsidies and rectification ledgers, avoiding truncation of critical information |
variables | Bind institution filing number, rectification ledger ID | Used to dynamically call exclusive data for corresponding institutions in the workflow, adapting to multi-institution parallel supervision scenarios |
| nodeId | Mark cross-department data pull nodes | Used to track different data source nodes for fire safety inspections and civil affairs statistics, facilitating workflow exception troubleshooting |
Three Common Configuration Mistakes
- Phenomenon: After importing an external JSON workflow, the text processing module cannot be found in the local workflow editor. Cause: The local workflow does not have the corresponding plugin permission enabled, or the custom node included in the imported JSON is not compatible with the current version.
- Phenomenon: After the workflow configuration is completed, it cannot be exported as a JSON file. Cause: The workflow draft has not been saved, or there are incompletely configured required nodes in the current workflow, causing the export function to be disabled.
- Phenomenon: After setting the search filter reference quota upper limit to 2000 entries, the token count for a single round of responses exceeds 3000. Cause: The threshold was not adjusted based on the field length of elderly care service documents. The field concatenation of structured documents far exceeds the expected token consumption, and calibration is required based on the actual length of business documents.
How to Confirm Proper Configuration
- Manually trigger the workflow, check whether the cross-department data pull node can correctly pull corresponding data from the elderly care service information platform and fire safety inspection records.
- Submit test elderly care institution filing materials, check whether the workflow's field extraction node can accurately match key fields such as institution names and bed counts.
- Adjust the search filter reference quota upper limit, use simulated inquiry statements for testing, and confirm that the token consumption of responses meets the expected threshold.
- View the workflow's failure alarm configuration, simulate input of abnormal data, and confirm that the alarm node can normally trigger notifications.
The values provided here are common starting points, and should be evaluated against local operational samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.